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The rapid and accurate detection of SARS-CoV-2 in environmental settings is crucial for effective public health management during the COVID-19 pandemic. This study compares the performance of the Reverse Transcription quantitative polymerase chain reaction (RT-qPCR) and the Reverse Transcription loop-mediated isothermal amplification (RT-LAMP) for SARS-CoV-2 detection from 100 surface samples collected in healthcare environments. The reference method, RT-qPCR, identified a percentage of 25% of positive samples, while RT-LAMP detected a percentage of 27% of positive surfaces. Our findings reveal a sensitivity of 32% and specificity of 75% for RT-LAMP, with a positive predictive value of 30% and a negative predictive value of 77%. The overall accuracy and concordance with RT-qPCR was 64% for both methods. Despite its lower sensitivity compared to RT-qPCR, RT-LAMP had an advantage due to its rapid screening and environmental surveillance, which is particularly useful for confirming negative results. These results underscore the potential of RT-LAMP not only as a valuable method in the environmental monitoring of SARS-CoV-2 but also as a system to control the sanitation process in ordinary and emergency conditions, providing further optimization and validation for its reliability in routine surveillance and outbreak response efforts.

Two Legionella-like isolates, 8cVS16T and 9fVS26, were isolated from a water distribution system (WDS) in a healthcare facility. Cells were Gram- and Ziehl Neelsen-stain-negative, rod-shaped, motile, and exhibited a blue-white fluorescence under Wood’s lamp at 365 nm. The strains grew in a range of 32–37 °C on BCYE with L-cysteine (Cys+), GVPC, and MWY agar medium, with a positive reaction for oxidase, catalase, and gelatinase. The dominant fatty acids were summed features 3 (C16:1ω7c/C16:1ω6c) (27.7%), C16:0 iso (17.5%), and C16:0 (16.3%), and Q13 as the major ubiquinone. The mip and rpoB gene sequences showed a similarity of 96.7% and 92.4%, with L. anisa (ATCC 35292T). The whole genomes sequencing (WGS) performed displayed a GC content of 38.21 mol% for both. The digital DNA-DNA hybridization (dDDH) analysis demonstrated the separation of the two strains from the phylogenetically most related L. anisa (ATCC 35292T), with ≤43% DNA-DNA relatedness. The Average Nucleotide Identity (ANI) between the two strains and L. anisa (ATCC 35292T) was 90.74%, confirming that the two isolates represent a novel species of the genus Legionella. The name proposed for this species is Legionella resiliens sp. nov., with 8cVS16T (=DSM 114356T = CCUG 76627T) as the type strain.